Environmental Change and Livelihood Activities in Hadejia-Nguru Wetlands of Yobe State, North East Nigeria
Bibliographic record
Abstract
The Hadejia-Nguru wetlands is an extensive area of flood plains located in the Sudano-Sahelian zone of north east Nigeria. The population rely heavily on natural resources for their livelihoods. In recent years, climatic vagaries, increasing populations and unregulated livelihood activities have significantly affected water and other resources availability and communities are faced with constant struggle of survival under a declining resource base. This study assessed the adverse effects of environmental change on resource users and how this influences their livelihood options. Understanding the perceptions, knowledge and practices of local resource users and what shapes their livelihood options is an area of critical importance that is currently under-researched in the area. This paper argues that to effectively influence policy and practice that support sustainable use of natural resources, it is important to not only understand resource user's knowledge and choices about their changing environment but how they utilize this knowledge in their actions and the overall impact on the environment. Mixed methods consisting of semi-structured questionnaire and Focus Group Discussions (FGD) based on two Participatory Rural Appraisal (PRA) tools (Village Timeline and Contextual Change) were utilized to solicit primary data. Environmental change in the area is accelerated by human activities and people have developed several local mechanisms of adapting to change. These adaptive measures could further be explored for developing policies and programs aimed at tackling the challenges of environmental change and resource decline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".